Four infrastructure considerations capable of making smart cities “smarter” and more resilient

With the passage of the $1.2 trillion Infrastructure Investment and Jobs Act, much-needed funds are starting to trickle down to states and cities. But how will localities spend their share?

While our nation’s roads, bridges, and highways need attention, the legislation also offers new opportunities for state and local agencies to lay the infrastructure of the future. And with two-thirds of the world’s population expected to live in cities by 2050, smart cities are a top priority.

However, the technologies enabling smart cities—including the internet of things (IoT), artificial intelligence (AI), and drones—are only as good as the infrastructure they run on. Cities will need wired and wireless networks to handle the massive amount of data sensors will generate. In addition, those networks must be secure, redundant, and resilient. And because state and local IT resources are finite, they must also be autonomous.

How can this modernized infrastructure be realized? Let’s look at four key areas underpinning smart cities capable of helping agencies prepare for the future.

1.AIOps: The next big thing in networking
Smart cities depend on a complex network of interconnected devices and sensors. Keeping an eye on what’s working and what’s not is an unenviable task. But instead of throwing more resources at the problem, imagine a network capable of predicting data bottlenecks or security issues before they occur. This is the premise and promise of applying artificial intelligence to IT operations (AIOps).

Powered by AI and machine learning, AIOps automates the previously cumbersome task of collecting and analyzing application data, logs and metrics. With this insight, operations teams can anticipate network issues, detect anomalies and gain the context needed to proactively fix issues—before performance is impacted.

For instance, if the connection drops between a highway congestion sensor and a smart traffic light, AIOps removes the human intervention needed to figure out what went wrong. Pulling masses of data from across the network, AIOps can quickly work out where the problem lies and identify a fix before the city slows to a crawl.

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